Methods, apparatus and articles of manufacture to estimate local market audiences of media content

ABSTRACT

Disclosed example audience measurement apparatus determine a first audience metric based on set-top box return path tuning data obtained from set-top boxes located in a first geographic area; determine a second audience metric from a portion of audience measurement data corresponding to a second geographic area, the portion of the audience measurement data associated with monitored sites in the second geographic area having second set-top box characteristics that correspond with first set-top box characteristics of the set-top boxes located in the first geographic area; determine ratios of (i) respective first audience metrics determined for respective demographic stratifications to (ii) corresponding second audience metrics determined for the respective demographic stratifications; and combine the ratios after multiplication with third audience metrics determined, for the respective demographic stratifications, from the audience measurement data to determine an audience exposure metric that estimates exposure to media in the first geographic area.

RELATED APPLICATION(S)

This patent arises from a continuation of U.S. patent application Ser.No. 15/891,076 (now U.S. Pat. No. ______), which is entitled “METHODS,APPARATUS AND ARTICLES OF MANUFACTURE TO ESTIMATE LOCAL MARKET AUDIENCESOF MEDIA CONTENT,” and which was filed on Feb. 7, 2018, which is acontinuation of U.S. patent application Ser. No. 15/416,790 (now U.S.Pat. No. 9,900,655), which is entitled “METHODS, APPARATUS AND ARTICLESOF MANUFACTURE TO ESTIMATE LOCAL MARKET AUDIENCES OF MEDIA CONTENT,” andwhich was filed on Jan. 26, 2017, which is a continuation of U.S. patentapplication Ser. No. 15/207,054 (now U.S. Pat. No. 9,578,361), which isentitled “METHODS, APPARATUS AND ARTICLES OF MANUFACTURE TO ESTIMATELOCAL MARKET AUDIENCES OF MEDIA CONTENT,” and which was filed on Jul.11, 2016, which is a continuation of U.S. patent application Ser. No.13/078,574 (now U.S. Pat. No. 9,420,320), which is entitled “METHODS,APPARATUS AND ARTICLES OF MANUFACTURE TO ESTIMATE LOCAL MARKET AUDIENCESOF MEDIA CONTENT,” and which was filed on Apr. 1, 2011. Priority to eachof U.S. patent application Ser. Nos. 13/078,574, 15/207,054, 15/416,790and 15/891,076 is claimed. U.S. patent application Ser. Nos. 13/078,574,15/207,054, 15/416,790 and 15/891,076 are hereby incorporated byreference in their respective entireties.

FIELD OF THE DISCLOSURE

This disclosure relates generally to audience measurement and, moreparticularly, to methods, apparatus and articles of manufacture toestimate local market audiences of media content.

BACKGROUND

Currently, there are 210 designated market areas (DMAs) for televisionaudience measurement in the United States, ranging in size from severalmillion households (e.g., New York, N.Y.) to a few thousand households(e.g., Zanesville, Ohio). DMAs are also referred to as local markets.For economic reasons, local market audience measurement typically relieson local audience measurement data having smaller sample sizes thannational-level audience measurement data, and/or that is collected usingless expensive, and potentially less accurate, measurement techniques(e.g., such as via diaries rather than automated people meters). Morerecently, return path data collected, measured and/or provided by cableand/or satellite set-top boxes offers an alternative method to measureaudiences of media content.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an example local market audience estimation system includingan example local market audience exposure estimator constructed inaccordance with the teachings of this disclosure.

FIG. 2 illustrates an example manner of implementing an example nationalaudience weighter included in the local market audience exposureestimator of FIG. 1.

FIG. 3 illustrates an example manner of implementing an example localaudience factorer included in the local market audience exposureestimator of FIG. 1.

FIG. 4 illustrates an example process that may be implemented usingmachine-readable instructions executed by one or more processors toimplement the example local market audience exposure estimator of FIG.1.

FIG. 5 illustrates an example process that may be implemented usingmachine-readable instructions executed by one or more processors toimplement the example national audience weighter of FIGS. 1 and/or 2.

FIG. 6 illustrates an example process that may be implemented usingmachine-readable instructions executed by one or more processors toimplement the example local audience factorer of FIGS. 1 and/or 3.

FIGS. 7A-D and 8A-D illustrates example local market audience exposuremetrics determined by the example local market audience estimationsystem of FIG. 1 for an example local market.

FIG. 9 is a schematic illustration of an example processing system thatmay be used and/or programmed to implement the example local marketaudience exposure estimator of FIG. 1, the example national audienceweighter of FIGS. 1 and/or 2, the example local audience factorer ofFIGS. 1 and/or 3, and/or the example machine-readable instructions ofFIGS. 4-6.

DETAILED DESCRIPTION

Example methods, apparatus and articles of manufacture to estimate localmarket audiences of media content are disclosed herein. An examplemethod disclosed herein determines a local audience exposure metricestimating exposure to media content in a local market. The localaudience exposure metric can correspond to, for example, a localaudience population estimate estimating a number of persons in the localmarket that have been exposed to the media context, or a local audienceratings estimate estimating a percentage of persons in the local marketthat have been exposed to the media content, etc. The example methodincludes weighting national audience measurement data based on localpopulation data to form weighted data. The example method also includesfactoring (e.g., scaling or otherwise processing based on one or morefactors) the weighted data based on the national audience measurementdata and local tuning data to determine the local audience exposuremetric.

In some examples, weighting the national audience measurement datacomprises weighting the national audience measurement based on a targetdemographic group represented in the local population data, and also oneor more of a target program, a target date, a target time-of-day, etc.In some examples, the local tuning data is local set-top box return pathtuning data, and factoring the weighted data includes determining afactor corresponding to a ratio of a first audience metric determinedfrom the local set-top box return path tuning data and a second audiencemetric determined from a cutback portion of the national audiencemeasurement data, and then scaling a third audience metric determinedfrom the weighted data based on the factor to determine the localaudience exposure metric. In some examples, these first, second andthird audience metrics are respective first, second and third audiencepopulation estimates, or respective first, second and third audienceratings estimates, etc. In some examples, the cutback portion of thenational audience measurement data corresponds to a portion of thenational audience measurement data associated with monitored siteshaving set-top box characteristics substantially similar to the localset-top box return path tuning data. Other examples of factoring theweighted data are also described hereinbelow.

A disclosed example apparatus to determine a local audience exposuremetric estimating exposure to media content in a local market includesan example national exposure weighter to weight national audiencemeasurement data based on local population data to form weighted data.The example apparatus also includes an example local audience factorerto factor (e.g., to scale or otherwise process based on one or morefactors) the weighted data based on the national audience measurementdata and local tuning data to determine the local audience exposuremetric. In some examples, the national exposure weighter includes anexample sampler to select a subset of the national audience measurementdata, and an example weighter to weight the subset based on a targetdemographic group represented in the local population data, and also oneor more of a target program, a target date, a target time-of-day, etc.In some examples, the local tuning data is local set-top box return pathtuning data, and the example local audience factorer includes: (1) anexample characterizer to impute characteristics of the local set-top boxreturn path tuning data; (2) an example cutback indicator to add cutbackindicators to the weighted data; (3) a first example estimator tocompute a demographic audience metric using the weighted data; (4) asecond example estimator to compute a cutback audience metric using aportion of the weighted data having a cutback indicator selected basedon the local set-top box return path tuning data; (5) a third exampleestimator to compute a set-top box audience metric using the localset-top box return path tuning data; and (4) a fourth example estimatorto combine the demographic audience metric, the cutback audience metricand the set-top box audience metric to form the local audience exposuremetric.

While return path data may be relatively inexpensive to obtain and/ormay enable the collection of relatively large quantities of audiencemeasurement data, return path data can be biased and/or incomplete. Withrespect to incompleteness, return path data may, for example, excludesections of the population (e.g., such as excluding non-subscribers to aparticular digital service providing the return path data), lackdemographic attributes, lack on/off indicators for the mediapresentation device coupled with the set-top box providing the returnpath data, lack information pertaining to which persons are in theviewing area and/or lack information regarding media contentviewing/consumption on devices in a subscriber's households notassociated with the set-top box. In contrast, traditional sample-basedaudience measurement techniques (e.g., diaries and/or automated peoplemeters) have comparatively higher costs and/or comparatively smallersample sizes, but are substantially less biased and providesubstantially more complete data.

The example methods, apparatus and articles of manufacture to estimatelocal market audiences of media content disclosed herein overcome atleast some of the limitations associated with local market audiencemeasurement based on just return path data or just traditionalsample-based audience measurement techniques. The examples disclosedherein leverage the strengths of return path data (e.g., large samplesize and low cost) and sample-based research (e.g., unbiased andcomplete) to obtain, at least under some circumstances, unbiased,detailed and continuous estimates of local market audiences at anaffordable cost. As described in greater detail below, the examplesdisclosed herein estimate local market audiences using a statisticalcombination of national sample-based audience measurement data, localreturn path data (or, more generally, local tuning data), and localpopulation and/or demographic data.

FIG. 1 illustrates an example local market audience estimation system100 to estimate, form, compute and/or otherwise generate local marketaudience measurement metrics 105 characterizing exposure to mediacontent in one or more local markets. The media content for which localmarket audience measurement metrics 105 are to be determined cancorrespond to any type of media content, such as television, cableand/or satellite broadcast programming, video-on-demand programming,radio broadcast programming, online/streaming media content, etc. Anynumber and/or type(s) of television audience measurement system(s) 110can be used to collect, measure and/or otherwise obtain example data 115representing audiences of media content. The television audiencemeasurement system(s) 110 can obtain the audience measurement data via,for example, people meters operating in statistically-selectedhouseholds, set-top boxes and/or other media devices (e.g., such asdigital video recorders, personal computers, tablet computer,smartphones, etc.) capable of monitoring and returning monitored datafor media content presentations, etc. In some examples, the audiencemeasurement system(s) 110, as well as the local market televisionaudience estimation system 100, are used by advertisers and/or contentproviders to measure and/or establish with scientific and/or verifiableaccuracy the reach of their advertising campaigns and/or media content.

As illustrated in FIG. 1, the example audience measurement system(s) 110obtain the example data 115 representative of audiences of media contentduring one or more survey time periods. The example data 115 of FIG. 1includes national audience measurement data 115A collected and/orobtained from, for example, people meters and/or other techniques formeasuring a national audience of media content, and local tuning data115B collected and/or obtained from, for example, return path dataprovided by cable and/or satellite set-top boxes (STBs) and/or othermedia devices. In the illustrated example of FIG. 1, the nationalaudience data 115 is assumed to include audience demographic informationand to characterize person-level exposure to media content. In contrast,the local tuning data 115B is assumed to not include audiencedemographic information and to characterize household-level (or, morespecifically, device-level or STB-level) exposure to media content.Furthermore, it is assumed that the amount of local tuning data 115Bsubstantially exceeds the amount of national audience data 115A (or atleast the portion of the national audience data 115A that corresponds toa particular local market). The example data 115, 115A and 115B can beimplemented by any number and/or type(s) of data structure(s), table(s),list(s) and/or record(s). The data 115, 115A and 115B can be stored onany number and/or type(s) of volatile and/or non-volatile memory(ies),memory device(s) and/or storage device(s).

To provide information representing the population of local markets, theexample local market audience estimation system 100 of FIG. 1 includeslocal population data 120 (also referred to as local universe estimates120). The example local population data 120 represents the demographicsof local markets and can be obtained from any source or combination ofsources providing demographic information for the local population(s)for which audience estimation is to be performed. The example localpopulation data 120 can be implemented by any number and/or type(s) ofdata structure(s), table(s), list(s) and/or record(s). The localpopulation data 120 can be stored on any number and/or type(s) ofvolatile and/or non-volatile memory(ies), memory device(s) and/orstorage device(s).

To generate and/or compute the example local market audience measurementmetrics 105, the example local market audience estimation system 100 ofFIG. 1 includes a local market audience exposure rater 125. The examplelocal market audience exposure estimator 125 of FIG. 1 statisticallycombines the national audience measurement data 115A, the local returnpath data 115B, and the local population and/or demographic data 120 togenerate and/or compute the local market television audience metrics105. In the illustrated example, to perform such statistical combining,the local market audience exposure estimator 125 includes an examplenational audience weighter 130 and an example local audience factorer135.

As described in greater detail below, the example national audienceweighter 130 of FIG. 1 samples the national audience data 115A andweights the samples national audience data 115A based on the localpopulation data 120 to determine weighted national audience data, alsoreferred to herein as simply weighted data. The weighted data forms aninitial estimate of the local audience of the media content. As such,the national audience weighter 130 uses any appropriate weightingtechnique to weight (e.g., scale, emphasize, deemphasize, etc.) thenational audience data 115A based on the demographic informationincluded the national audience data 115A and the local population data120 such that the resulting weighted data is representative of thedemographics of the local market under consideration.

However, audience exposure to media content may be influenced by localcharacteristics (e.g., such as local preferences, local on-airpersonalities, etc.) that are not functions of demographics alone.Unlike the national audience data 115A, the local tuning data 115B isobtained by, for example, STB return path data for households in thelocal market. As such, the local tuning data 115B can reflect thepreferences in the local market that are not functions of thedemographics alone. However, the local tuning data 115B by itself may beinsufficient to characterize the local audience because the local tuningdata 115B does not include demographic information, is at the householdor device level rather than the person level, and reflects the viewingof only those local sites providing the local tuning data 115B (e.g.,such as only those households having STBs capable of providing thereturn path data forming the local tuning data 115B). Accordingly, andas described in greater detail below, the example local audiencefactorer 135 of FIG. 1 factors (e.g., scales and/or otherwise processesusing one or more factors) the weighted data determined by the nationalaudience weighter 130 (which includes demographic information, is at theperson level and represents audience exposure across different mediacontent presentation platforms) based on the local tuning data 115Bobtained for the local market under consideration (which can representlocal preferences not accounted for by demographics alone) to determinethe local market audience metrics 105.

An example implementation of the national audience weighter 130 of FIG.1 is illustrated in FIG. 2. The example national audience weighter 130of FIG. 2 includes an example sampler 205 to sample the nationalaudience measurement data 115A to produce a data subset that is relevantto the local market. For example, the statistically selected panel ofhouseholds containing the people meters that provide the nationalaudience measurement data 115A can change over time. Thus, the sampler205 can employ any appropriate sampling technique to sample the nationalaudience measurement data 115A to select only that data corresponding tohouseholds in the current statistically selected panel and to excludedata corresponding to obsolete households no longer in the statisticallyselected panel. Additionally or alternatively, the sampler 205 canemploy any appropriate sampling technique to sample only the portions ofthe national audience measurement data 115A having demographic relevanceto the local market under consideration. Other type(s) of data samplingcan additionally or alternatively be implemented by the sampler 205.

The example national audience weighter 130 of FIG. 2 also includes anexample weighter 210 to weight the sampled national audience measurementdata 115A obtained from the sampler 205 to provide an initial estimateof audience measurement data for the local market under consideration.For example, the weighter 210 can use any appropriate technique tostatistically weight (e.g., scale, emphasize, deemphasize, etc.) thesampled national audience measurement data 115A to account fordifferences between the size and/or demographic makeup of the nationalaudience measurement data 115A and the size and/or demographic makeup ofthe local market as represented by the local population data 120. Theresult of the weighting performed by the weighter 210 is weightednational audience measurement data 215 that can be used as an initialestimate of the local audience measurement data for the particular localmarket under consideration.

An example implementation of the local audience factorer 135 of FIG. 1is illustrated in FIG. 3. The example local audience factorer 135 ofFIG. 3 uses the weighted national audience measurement data 215determined by the weighter 130 of FIG. 2 and the local tuning data 115B(e.g., which is local STB return path data 115B in the illustratedexample) to determine the local market audience metrics 105. In theillustrated example of FIG. 3, the local audience factorer 135 includesan example demographic audience estimator 305 to determine (e.g.,compute) an initial demographic audience metric from the weightednational audience measurement data 215 for a particular demographicstratification. For example, for a particular demographicstratification, i, the corresponding initial demographic audiencemetric, D_(i), determined by the demographic audience estimator 305 cancorrespond to an audience population estimate estimating a number ofpersons in the local market and the particular demographicstratification, i, that have been exposed to the media context. Asanother example, for a particular demographic stratification, i, thecorresponding initial demographic audience metric, D_(i), determined bythe demographic audience estimator 305 can correspond to an audienceratings estimate estimating a percentage of persons in the local marketand the particular demographic stratification, i, that have been exposedto the media content, etc. Examples of demographic stratificationsinclude, but are not limited to, gender stratifications, agestratifications, income stratifications, etc., and/or any combination(s)thereof.

The local audience factorer 135 also includes an example characterizer310 and an example STB audience estimator 315 to determine a firstfactor to be used to factor the weighted national audience data 215 todetermine the local market audience metrics 105. In the illustratedexample, the characterizer 310 is to impute characteristics of the localSTB return path tuning data 115B. As noted above, the local STB returnpath tuning data 115B (or, more generally, the local tuning data 115B)generally does not include demographic information. As such, to enablethe local STB return path tuning data 115B to be used to factor theweighted national audience data 215 for a particular demographicstratification, the characterizer 310 adds demographic information tothe local STB return path tuning data 115B. The characterizer 310 canemploy any appropriate technique or techniques to add demographicinformation to the local STB return path tuning data 115B. For example,the characterizer 310 can add demographic information obtained fromsurveys and/or other sources of information for the householdscontaining the STBs providing the local STB return path tuning data115B. Additionally or alternatively, the characterizer 310 can bootstrapthe demographic information by inferring the demographic information fora particular household based on the types of media content included inthe STB return path tuning data 115B for that household.

The STB audience estimator 315 of FIG. 3 determines (e.g., computes) anSTB audience metric from the local STB return path data 115B for aparticular demographic stratification. For example, for a particulardemographic stratification, i, the corresponding STB audience metric,S_(i), determined by the STB audience estimator 315 can correspond to anaudience population estimate estimating a number of households among thehouseholds represented in the STB return path data 115B and in theparticular demographic stratification, i, that have been exposed to themedia context. As another example, for a particular demographicstratification, i, the corresponding STB audience metric, S_(i),determined by the STB audience estimator 315 can correspond to anaudience ratings estimate estimating a percentage of households amongthe households represented in the STB return path data 115B and in theparticular demographic stratification, i, that have been exposed to themedia content, etc.

The local audience factorer 135 further includes an example cutbackindicator appender 320 and an example cutback audience estimator 325 todetermine a second factor to be used to factor the weighted nationalaudience data 215 to determine the local market audience metrics 105.The STB audience metric determined by the STB audience estimator 315 incombination with the characterizer 320 represents, for example, localmedia content preferences that are not accounted for by demographicsalone, which can be used to modify the initial demographic audiencemetric, D_(i), determined from the weighted national audiencemeasurement data 215. However, the STB audience metric is based on dataobtained from only a subset of the local audience households containingthe particular type(s) of STB equipment providing the return path data.Thus, to determine a factor for adjusting the initial demographicaudience metric, D_(i), based on the STB audience metric S_(i), thecutback indicator appender 320 and the cutback audience estimator 325determine a cutback audience metric from only those portion(s) theweighted national audience data 215 associated with type(s) of STBequipment substantially similar to that associated with the local STBreturn path data 115B. Selection of the appropriate portion of theweighted national audience data 215 associated with a particular type ofSTB equipment is facilitated by the use of cutback indicators. A cutbackindicator represents a particular (e.g., unique) type of STB equipmentor set of STB characteristics. Accordingly, the cutback indicatorappender 320 appends cutback indicators to the weighted nationalaudience data 215 to indicate the type of STB equipment or set of STBcharacteristics associated with entries in the weighted nationalaudience data 215.

The cutback audience estimator 325 of FIG. 3 determines (e.g., computes)a cutback audience metric from the weighted national audience data 215for a particular demographic stratification and particular cutbackcategory associated with the local return path data 115B. For example,for a particular demographic stratification, i, the correspondingcutback audience metric, C_(i), determined by the cutback audienceestimator 325 can correspond to an audience population estimateestimating a number of households among the households in the weightednational audience data 215 having the same type of STB equipment or setof STB characteristics as the local return path data 115B and in theparticular demographic stratification, i, that have been exposed to themedia context. As another example, for a particular demographicstratification, i, the corresponding cutback audience metric, C_(i),determined by the cutback audience estimator 325 can correspond to anaudience ratings estimate estimating a percentage of households amongthe households in the weighted national audience data 215 having thesame type of STB equipment or set of STB characteristics as the localreturn path data 115B and in the particular demographic stratification,i, that have been exposed to the media content, etc.

In the illustrated example of FIG. 3, the local audience factorer 135includes an example local market estimator 330 to process thedemographic audience metric, D_(i), the STB audience metric, S_(i), andthe cutback audience metric, C_(i), described above to determinefactor(s) for use in factoring the weighted national audience data 215to determine the local market audience metrics 105. In some examples,for a particular demographic stratification, the local audience factorer135 scales the initial demographic audience metric, D_(i), by a factorthat is a ratio of the STB audience metric, S_(i), and the cutbackaudience metric, C_(i) to determine a local market audience metric forthis particular demographic stratification, i. Mathematically, thefactoring (e.g., scaling) performed by the local market estimator 330 todetermine a local market audience metric, A_(i), for a particulardemographic stratification, i, is represented by Equation 1:

$\begin{matrix}{A_{i} = {{D_{i}F_{i}} = {D_{i}( \frac{S_{i}}{C_{i}} )}}} & {{Equation}\mspace{14mu} 1}\end{matrix}$

In Equation 1, the factor F_(i)=S_(i)/C_(i) factors (e.g., scales) theinitial demographic audience metric, D_(i), to account for localcharacteristics that are not a function of demographics alone. Theexamples disclosed herein are not limited to any particular technique(s)for determining the demographic audience metric(s), D_(i), the STBaudience metric(s), S_(i), and the cutback audience metric(s), C_(i).

In some examples, the local market estimator 330 determines an overall(also referred to as integrated) local market audience metric, A, bysumming the local market audience metric(s), A_(i), for all appropriatedemographic stratifications represented in the local market.Mathematically, this is represented by Equation 2:

$\begin{matrix}{A = {{\sum\limits_{i}A_{i}} = {{\sum\limits_{i}{D_{i}F_{i}}} = {\sum\limits_{i}{D_{i}( \frac{S_{i}}{C_{i}} )}}}}} & {{Equation}\mspace{14mu} 2}\end{matrix}$

In some examples, the local audience factorer 135 can restrict thefactor F_(i) to be within upper and lower limits U_(i) and L_(i),respectively, which may be the same or different for differentdemographic stratifications. These upper and lower limits can preventexcessive variation in the factor Fi that may occur, for example, if Ciis very small, resulting in an unrealistically large value of Fi.

In some examples, the local market audience metric, A_(i), is determinedbased on rewriting Equation 1 as Equation 3:

$\begin{matrix}{A_{i} = {{D_{i}( \frac{S_{i}}{C_{i}} )} = {{S_{i}( \frac{D_{i}}{C_{i}} )} = {{S_{i}( \frac{D_{i}}{P} )}( \frac{P}{H_{t}} )( \frac{H_{t}}{C_{i}} )}}}} & {{Equation}\mspace{14mu} 3}\end{matrix}$

In Equation 3, the quantity D_(i)/P is an audience participation factor,the quantity P/H_(t) is an audience member per household factor, and thequantity H_(t)/C_(i) is a total households against cutback ratingfactor. In some examples, the local audience factorer 135 determines thelocal market audience metric, A_(i), based on the quantities in Equation3 instead of directly via Equation 1 to, for example, enable one or moreof these quantities to be subjected to limits reflecting the particularaudience measurement environment.

In some examples, the local audience factorer 135 includes an examplelocal market adjuster 335 to adjust determination of the local marketaudience metrics 105 based on information, such as local audiencemeasurement data, different from and in addition to the local STB returnpath data 115B (or, more generally, the local tuning data 115B). Forexample, such additional information can include local audiencemeasurement data obtained from people meters and/or similar audiencemeasurement equipment for the particular local market, on/off indicatorsto indicate whether media presentation devices (e.g., televisions)coupled to the STBs providing the return path data 115B are turned on oroff, etc. For example, the local market adjuster 335 can determine thelocal market audience metric, A_(i), for a particular demographicstratification, i, by adjusting and/or scaling the factor F_(i) asrepresented by Equation 4:

$\begin{matrix}{A_{i} = {{D_{i} \times ( {g_{i} \times {{adj}( F_{i} )}} )} = {D_{i} \times ( {g_{i} \times {{adj}( \frac{S_{i}}{C_{i}} )}} )}}} & {{Equation}\mspace{14mu} 4}\end{matrix}$

In Equation 4, the quantity gi represents a gain to be used to scale thefactor F_(i), and the function adj(•) represents an adjustment to beperformed on the factor F_(i). For example, the function adj(•) caninvolve raising the factor F_(i) to a power to, for example, enhancedifferences between the local market audience metrics, A_(i), fordifferent demographic stratifications. The examples disclosed herein arenot limited to any particular technique(s) for determining the gaing_(i) and/or the adjustment function adj(•).

In some examples, the local market adjuster 335 determines an overall(also referred to as integrated) local market audience metric, A, bysumming, after adjustment, the local market audience metric, A_(i), forall appropriate demographic stratifications represented in the localmarket. Mathematically, this is represented by Equation 5:

$\begin{matrix}{A = {{\sum\limits_{i}A_{i}} = {{\sum\limits_{i}{D_{i} \times ( {g_{i} \times {{adj}( F_{i} )}} )}} = {\sum\limits_{i}{D_{i} \times ( {g_{i} \times {{adj}( \frac{S_{i}}{C_{i}} )}} )}}}}} & {{Equation}\mspace{14mu} 5}\end{matrix}$

Although the preceding examples refer to STB return path data andassociated STB audience metric estimation, the examples disclosed hereinare not limited thereto. For example, the STBs referred to above can bereplaced by any media device or devices capable of providing mediacontent and reporting media contact measurement data associatedtherewith.

While example manners of implementing the local market audience exposurerater 125, the example national audience weighter 130 and the examplelocal audience factorer 135 of FIG. 1 have been illustrated in FIGS.1-3, one or more of the elements, processes and/or devices illustratedin FIGS. 1-3 may be combined, divided, re-arranged, omitted, eliminatedand/or implemented in any other way. Further, the example sampler 205,the example weighter 210, the example demographic audience estimator305, the example characterizer 310, the example STB audience estimator315, the example cutback indicator appender 320, the example cutbackaudience estimator 325, the example local market estimator 330, theexample local market adjuster 335 and/or, more generally, the examplenational audience weighter 130, the example local audience factorer 135and/or the example local market audience exposure rater 125 of FIGS. 1-3may be implemented by hardware, software, firmware and/or anycombination of hardware, software and/or firmware. Thus, for example,any of the example sampler 205, the example weighter 210, the exampledemographic audience estimator 305, the example characterizer 310, theexample STB audience estimator 315, the example cutback indicatorappender 320, the example cutback audience estimator 325, the examplelocal market estimator 330, the example local market adjuster 335and/or, more generally, the example national audience weighter 130, theexample local audience factorer 135 and/or the example local marketaudience exposure rater 125 could be implemented by one or morecircuit(s), programmable processor(s), application specific integratedcircuit(s) (ASIC(s)), programmable logic device(s) (PLD(s)) and/or fieldprogrammable logic device(s) (FPLD(s)), etc. When any of the appendedapparatus claims are read to cover a purely software and/or firmwareimplementation, at least one of the example local market audienceexposure rater 125, the example national audience weighter 130, theexample local audience factorer 135, the example sampler 205, theexample weighter 210, the example demographic audience estimator 305,the example characterizer 310, the example STB audience estimator 315,the example cutback indicator appender 320, the example cutback audienceestimator 325, the example local market estimator 330 and/or the examplelocal market adjuster 335 are hereby expressly defined to include atangible computer readable medium such as a memory, digital versatiledisk (DVD), compact disk (CD), etc., storing such software and/orfirmware. Further still, the example local market audience exposurerater 125, the example national audience weighter 130 and/or the examplelocal audience factorer 135 of FIGS. 1-3 may include one or moreelements, processes and/or devices in addition to, or instead of, thoseillustrated in FIGS. 1-3, and/or may include more than one of any or allof the illustrated elements, processes and devices.

Flowcharts representative of example processes corresponding to examplemachine readable instructions that may be executed to implement theexample local market audience exposure rater 125, the example nationalaudience weighter 130, the example local audience factorer 135, theexample sampler 205, the example weighter 210, the example demographicaudience estimator 305, the example characterizer 310, the example STBaudience estimator 315, the example cutback indicator appender 320, theexample cutback audience estimator 325, the example local marketestimator 330 and/or the example local market adjuster 335 are shown inFIGS. 4-6. In these examples, the machine readable instructionsrepresented by each flowchart may comprise one or more programs forexecution by a processor, such as the processor 912 shown in the exampleprocessing system 900 discussed below in connection with FIG. 9.Alternatively, the entire program or programs and/or portions thereofimplementing one or more of the processes represented by the flowchartsof FIGS. 4-6 could be executed by a device other than the processor 912(e.g., such as a controller and/or any other suitable device) and/orembodied in firmware or dedicated hardware (e.g., implemented by anASIC, a PLD, an FPLD, discrete logic, etc.). Also, one or more of themachine readable instructions represented by the flowchart of FIGS. 4-6may be implemented manually. Further, although the example machinereadable instructions are described with reference to the flowchartsillustrated in FIGS. 4-6, many other techniques for implementing theexample methods and apparatus described herein may alternatively beused. For example, with reference to the flowcharts illustrated in FIGS.4-6, the order of execution of the blocks may be changed, and/or some ofthe blocks described may be changed, eliminated, combined and/orsubdivided into multiple blocks.

As mentioned above, the example processes of FIGS. 4-6 may beimplemented using coded instructions (e.g., computer readableinstructions) stored on a tangible computer readable medium such as ahard disk drive, a flash memory, a read-only memory (ROM), a CD, a DVD,a cache, a random-access memory (RAM) and/or any other storage media inwhich information is stored for any duration (e.g., for extended timeperiods, permanently, brief instances, for temporarily buffering, and/orfor caching of the information). As used herein, the term tangiblecomputer readable medium is expressly defined to include any type ofcomputer readable storage and to exclude propagating signals.Additionally or alternatively, the example processes of FIGS. 4-6 may beimplemented using coded instructions (e.g., computer readableinstructions) stored on a non-transitory computer readable medium, suchas a flash memory, a ROM, a CD, a DVD, a cache, a random-access memory(RAM) and/or any other storage media in which information is stored forany duration (e.g., for extended time periods, permanently, briefinstances, for temporarily buffering, and/or for caching of theinformation). As used herein, the term non-transitory computer readablemedium is expressly defined to include any type of computer readablemedium and to exclude propagating signals. Also, as used herein, theterms “computer readable” and “machine readable” are consideredequivalent unless indicated otherwise.

Example machine readable instructions 400 that may be executed toimplement the example local market audience exposure rater 125 of FIG. 1are represented by the flowchart shown in FIG. 4. With reference to thepreceding figures, the machine readable instructions 400 of FIG. 4 beginexecution at block 405 at which the national audience weighter 130included in the local market audience exposure rater 125 weights thatnational audience measurement data 115A based on the local populationdata 120 to determine the weighted national audience measurement data215. As described above, the weighted national audience measurement data215 can be used as an initial estimate of local audience measurementdata for the particular local market under consideration.

At block 410, the local audience factorer 135 included in the localmarket audience exposure rater 125 computes scaling factor(s) (e.g., Ffor the overall/integrated population, and/or F_(i) for one or moredemographic stratifications, i) from the national audience measurementdata 115A and the local population data 120, as described above. Atblock 415, the local audience factorer 135 factors (e.g., scales orotherwise processes using factor(s)) the weighted national audiencemeasurement data 215 to determine the local market audience metric(s)105 for the overall/integrated population and/or one or more demographicstratifications of the local market.

Example machine readable instructions 500 that may be executed toimplement the example national audience weighter 130 of FIGS. 1 and 2,and/or the processing at block 405 of FIG. 4, are illustrated in FIG. 5.With reference to the preceding figures, the machine readableinstructions 500 of FIG. 5 begin execution at block 505 at which thesampler 205 included in the national audience weighter 130 samples thenational audience measurement data 115A to obtain a subset of the datathat is relevant to the local market under consideration, as describedabove. At block 510, the weighter 210 included in the national audienceweighter 130 weights the subset of the national audience measurementdata 115A obtained at block 505 based on the local population data 120to determine the weighted national audience measurement data 215, asdescribed above. For example, in the case of determining audiencemetrics for television programming, at block 510 the national audienceweighter 130 can weight the subset of the national audience measurementdata 115A to reflect a target demographic group represented in the localpopulation data 120, as well as a target program, a target date on whichthe program was broadcast, a target time-of-day at which the program wasbroadcast, etc.

Example machine readable instructions 600 that may be executed toimplement the example local audience factorer 135 of FIGS. 1 and 3,and/or the processing at blocks 410-415 of FIG. 4, are illustrated inFIG. 6. With reference to the preceding figures, the machine readableinstructions 600 of FIG. 6 begin execution at block 605 at which thecharacterizer 310 included in the local audience factorer 135 imputesdemographic characteristics of the local tuning data 115B, as describedabove, to yield local tuning data 610 containing demographiccharacteristics. In the illustrated example, the imputed demographiccharacteristics correspond to the demographic stratifications present inthe local population data 120. At block 615, the cutback indicatorappender 320 included in the local audience factorer 135 appends cutbackindicators to the weighted national audience measurement data 215, asdescribed above, to yield weighted national audience measurement data620 containing cutback indicators.

At block 625, the demographic audience estimator 305 included in thelocal audience factorer 135 determines (e.g., computes) initialdemographic audience metric(s), D_(i), from the weighted nationalaudience measurement data 215 for the overall/integrated populationand/or one or more demographic stratifications, i, of the local market,as described above. At block 630, the cutback audience estimator 325included in the local audience factorer 135 determines (e.g., computes)the cutback audience metric(s), C_(i), from the weighted nationalaudience measurement data 620 for the overall/integrated populationand/or one or more demographic stratifications, i, of the local market,as described above. At block 640, the STB audience estimator 315included in the local audience factorer 135 determines (e.g., computes)the STB audience metric(s), S_(i), from the local STB return path data610 for the overall/integrated population and/or one or more demographicstratifications, i, of the local market, as described above.

At block 640, the local market estimator 330 included in the localaudience factorer 135 processes the initial demographic audiencemetric(s), D_(i), the cutback audience metric(s), C_(i), and the STBaudience metric(s), S_(i), determined at blocks 625-635 to determinelocal market audience metric(s), A_(i), for one or more demographicstratifications, i, of the local market, as described above. At block645, the local market estimator 330 determines a local market audiencemetric, A, by, for example, summing the local market audience metric(s),A_(i), determined at block 645, as described above. At block 650, thelocal market adjuster 335 included in the local audience factorer 135adjusts, if appropriate, the local market audience metric(s) A_(i)and/or A, as described above.

Example local market audience exposure metrics 105 determined by theexample local market audience estimation system 100 of FIG. 1 for anexample local market are illustrated in FIGS. 7A-D and 8A-D. Table 705of FIG. 7A illustrates a first example operation of the local marketaudience estimation system 100 to determine a local market audienceexposure metric 105 that is an overall/integrated local audiencepopulation estimate A (e.g., which is equivalent to selecting a singledemographic stratification covering the entire local population) for aparticular broadcast program and a particular day/time. Table 705illustrates weighting national audience measurement data (referred to asnational people meter (NPM) data in the figures) and calculation of theinitial local audience metric (e.g., population estimate), D, from theweighted national audience measurement data. Table 705 also illustratescalculation of the cutback audience metric (e.g., population estimate),C, and the STB audience metric (e.g., population estimate), S, as wellas the factor, F=S/C and its upper and lower limits, for the illustratedexample. Table 705 further illustrates calculation of theoverall/integrated local audience population estimate as A=D×S/C, asdescribed above.

Table 710 of FIG. 7B illustrates a second example operation of the localmarket audience estimation system 100 to determine local market audienceexposure metrics 105 that are local audience population estimates A_(i)for three demographic stratifications i. Table 710 illustratescalculation of the initial local audience metrics (e.g., populationestimates), D_(i), the cutback audience metrics (e.g., populationestimates), C_(i), the STB audience metrics (e.g., populationestimates), S_(i), and the factors, F_(i)=S_(i)/C_(i) or the threedemographic stratifications i. In the illustrated example, the factorsF_(i) have different upper and lower limits for each demographicstratifications i. Table 710 also illustrates calculation of the localmarket audience metrics (e.g., population estimates) A_(i) and A basedon Equation 1 and Equation 2.

Table 715 of FIG. 7C illustrates a third example operation of the localmarket audience estimation system 100 to determine local market audienceexposure metrics 105 that are local audience population estimates A_(i)for three demographic stratifications i, which are adjusted based on anadjustment function adj(•). The operations illustrated in Table 715 aresimilar to operations illustrated in FIG. 710, except that Table 715further illustrates adjustment of the factors F_(i). The adjustmentfunction adj(•) utilized in Table 715 is to raise each factor F_(i) toan exponent represented by the illustrated amplification constant.

Table 720 of FIG. 7D illustrates a fourth example operation of the localmarket audience estimation system 100 to determine local market audienceexposure metrics 105 that are local audience population estimates A_(i)for three demographic stratifications i, which are adjusted based on theadjustment function adj(•) of Table 715, as well as gains g_(i). Theoperations illustrated in Table 720 are similar to operationsillustrated in FIG. 715, except that Table 720 further illustratesmultiplying the adjusted factors F_(i) by the gains g_(i). In theillustrated example, different gain factors g_(i) are associated witheach demographic stratifications i.

FIGS. 8A-D include Tables 805, 810, 815 and 820 that illustrate exampleoperations of the local market audience estimation system 100 similar tothe respective examples of Tables 705, 710, 715 and 720. However, inTables 805, 810, 815 and 820, the determined local market audienceexposure metrics 105 are local audience ratings estimates A and A_(i),whereas the local market audience exposure metrics 105 determined inTables 705, 710, 715 and 720 are local audience population estimates Aand A_(i).

FIG. 9 is a block diagram of an example processing system 900 capable ofimplementing the apparatus and methods disclosed herein. The processingsystem 900 can be, for example, a server, a personal computer, apersonal digital assistant (PDA), an Internet appliance, a DVD player, aCD player, a digital video recorder, a personal video recorder, a settop box, or any other type of computing device.

The system 900 of the instant example includes a processor 912 such as ageneral purpose programmable processor. The processor 912 includes alocal memory 914, and executes coded instructions 916 present in thelocal memory 914 and/or in another memory device. The processor 912 mayexecute, among other things, the machine readable instructionsrepresented in FIGS. 4-6. The processor 912 may be any type ofprocessing unit, such as one or more Intel® and/or ARM® microprocessors,and/or one or more PIC® microcontrollers, etc. Of course, otherprocessors from other families are also appropriate.

The processor 912 is in communication with a main memory including avolatile memory 918 and a non-volatile memory 920 via a bus 922. Thevolatile memory 918 may be implemented by Static Random Access Memory(SRAM), Synchronous Dynamic Random Access Memory (SDRAM), Dynamic RandomAccess Memory (DRAM), RAMBUS Dynamic Random Access Memory (RDRAM) and/orany other type of random access memory device. The non-volatile memory920 may be implemented by flash memory and/or any other desired type ofmemory device. Access to the main memory 918, 920 is typicallycontrolled by a memory controller (not shown).

The processing system 900 also includes an interface circuit 924. Theinterface circuit 924 may be implemented by any type of interfacestandard, such as an Ethernet interface, a universal serial bus (USB),and/or a third generation input/output (3GIO) interface.

One or more input devices 926 are connected to the interface circuit924. The input device(s) 926 permit a user to enter data and commandsinto the processor 912. The input device(s) can be implemented by, forexample, a keyboard, a mouse, a touchscreen, a track-pad, a trackball,an isopoint and/or a voice recognition system.

One or more output devices 928 are also connected to the interfacecircuit 924. The output devices 928 can be implemented, for example, bydisplay devices (e.g., a liquid crystal display, a cathode ray tubedisplay (CRT)), by a printer and/or by speakers. The interface circuit924, thus, typically includes a graphics driver card.

The interface circuit 924 also includes a communication device such as amodem or network interface card to facilitate exchange of data withexternal computers via a network (e.g., an Ethernet connection, adigital subscriber line (DSL), a telephone line, coaxial cable, acellular telephone system, etc.).

The processing system 900 also includes one or more mass storage devices930 for storing machine readable instructions and data. Examples of suchmass storage devices 930 include floppy disk drives, hard drive disks,compact disk drives, digital versatile disk (DVD) drives, flash drives,etc. In some examples, the mass storage device 930 may store one or moreof the data 115, 115A, 115B, 120 and/or 215, and/or the local audiencemetrics 105. Additionally or alternatively, in some examples thevolatile memory 918 may store one or more of the data 115, 115A, 115B,120 and/or 215, and/or the local audience metrics 105.

The coded instructions 932 of FIGS. 4-6 may be stored in the massstorage device 930, in the volatile memory 918, in the non-volatilememory 920, in the local memory 914 and/or on a removable storagemedium, such as a CD or DVD 932.

As an alternative to implementing the methods and/or apparatus describedherein in a system such as the processing system of FIG. 9, the methodsand or apparatus described herein may be embedded in a structure such asa processor and/or an ASIC (application specific integrated circuit).

Finally, although certain example methods, apparatus and articles ofmanufacture have been described herein, the scope of coverage of thispatent is not limited thereto. On the contrary, this patent covers allmethods, apparatus and articles of manufacture fairly falling within thescope of the appended claims either literally or under the doctrine ofequivalents.

What is claimed is:
 1. An audience measurement apparatus comprising:memory including computer readable instructions; and a processor toexecute the instructions to at least: determine a first audience metricbased on set-top box return path tuning data obtained from a pluralityof set-top boxes located in a first geographic area; determine a secondaudience metric from a portion of audience measurement datacorresponding to a second geographic area different from the firstgeographic area, the portion of the audience measurement data associatedwith monitored sites in the second geographic area having second set-topbox characteristics that correspond with first set-top boxcharacteristics of the plurality of set-top boxes located in the firstgeographic area; determine a plurality of ratios of (i) respective firstaudience metrics determined for respective demographic stratificationsto (ii) corresponding second audience metrics determined for therespective demographic stratifications; and combine the plurality ofratios after multiplication with third audience metrics determined, forthe respective demographic stratifications, from the audiencemeasurement data to determine an audience exposure metric that estimatesexposure to media in the first geographic area.
 2. The audiencemeasurement apparatus of claim 1, wherein the audience measurement datais second audience measurement data, and the processor is to weightfirst audience measurement data associated with the second geographicarea, the processor to weight the first audience measurement data basedon population data associated with the first geographic area to form thesecond audience measurement data.
 3. The audience measurement apparatusof claim 1, wherein the first geographic area is associated with a localaudience located in a local market, and the second geographic area isassociated with a national audience of the media.
 4. The audiencemeasurement apparatus of claim 1, wherein the audience exposure metricincludes at least one of an audience population estimate of a number ofpersons in the first geographic area that have been exposed to themedia, or an audience ratings estimate of a percentage of persons in thefirst geographic area that have been exposed to the media.
 5. Theaudience measurement apparatus of claim 1, wherein the audiencemeasurement data is second audience measurement data, and the processoris to adjust the plurality of ratios based on first audience measurementdata associated with the first geographic area and that is differentfrom the set-top box return path tuning data.
 6. The audiencemeasurement apparatus of claim 5, wherein the plurality of ratiosincludes a first ratio, and the processor is to: raise the first ratioto a power to determine an adjusted ratio; and scale the adjusted ratioby a gain value, the power and the gain value to be determined based onthe first audience measurement data.
 7. The audience measurementapparatus of claim 1, wherein the respective ones of the plurality ofratios are limited to be between a lower limit and an upper limit.
 8. Anaudience measurement apparatus comprising: memory including computerreadable instructions; and a processor to execute the instructions to atleast: determine a first audience metric based on audience measurementdata associated with a second geographic area different from a firstgeographic area; determine a second audience metric from a portion ofthe audience measurement data identified to be associated with monitoredsites in the second geographic area having second set-top boxcharacteristics that correspond with first set-top box characteristicsof a plurality of set-top boxes located in the first geographic area;determine a plurality of ratios of (i) respective first audience metricsdetermined for respective demographic stratifications to (ii)corresponding second audience metrics determined for the respectivedemographic stratifications; and combine the plurality of ratios aftermultiplication with third audience metrics determined, for therespective demographic stratifications, from set-top box return pathtuning data to determine an audience exposure metric that estimatesexposure to media in the first geographic area, the set-top box returnpath tuning data obtained from the plurality of set-top boxes located inthe first geographic area.
 9. The audience measurement apparatus ofclaim 8, wherein the audience measurement data is second audiencemeasurement data, and the processor is to weight first audiencemeasurement data associated with the second geographic area, theprocessor to weight the first audience measurement data based onpopulation data associated with the first geographic area to form thesecond audience measurement data.
 10. The audience measurement apparatusof claim 8, wherein the first geographic area is associated with a localaudience located in a local market, and the second geographic area isassociated with a national audience of the media.
 11. The audiencemeasurement apparatus of claim 8, wherein the audience exposure metricincludes at least one of an audience population estimate of a number ofpersons in the first geographic area that have been exposed to themedia, or an audience ratings estimate of a percentage of persons in thefirst geographic area that have been exposed to the media.
 12. Theaudience measurement apparatus of claim 8, wherein to combine theplurality of ratios, the processor is to: multiply respective ones ofthe plurality of ratios by corresponding ones of the third audiencemetrics to determine fourth audience metrics; and sum the fourthaudience metrics to determine the audience exposure metric.
 13. Theaudience measurement apparatus of claim 8, wherein the plurality ofratios includes a first ratio, and the processor is to combine a secondratio, a third ratio and a fourth ratio to determine the first ratio.14. The audience measurement apparatus of claim 13, wherein the secondratio includes a fifth ratio of the first audience metric to a number ofaudience members, the third ratio includes a sixth ratio of the numberof audience members to a number of households, and the fourth ratioincludes a seventh ratio of the number of household to the secondaudience metric.
 15. An audience measurement apparatus comprising:memory including computer readable instructions; and a processor toexecute the instructions to at least: weight audience measurement dataassociated with a first geographic area based on population dataassociated with a second geographic area different from the firstgeographic area to form weighted data; determine a plurality of ratiosof (i) respective first audience metrics determined, for respectivedemographic stratifications, from set-top box return path tuning dataassociated with the second geographic area to (ii) corresponding secondaudience metrics determined, for the respective demographicstratifications, from corresponding cutback portions of the audiencemeasurement data identified to be associated with monitored sites in thefirst geographic area having first set-top box characteristics thatcorrespond with second set-top box characteristics of set-top boxequipment that provided the set-top box return path tuning data; andcombine the plurality of ratios after multiplication with third audiencemetrics determined, for the respective demographic stratifications, fromthe weighted data to determine an audience exposure metric thatestimates exposure to media in the second geographic area.
 16. Theaudience measurement apparatus of claim 15, wherein the first geographicarea is associated with a national audience of the media, and the secondgeographic area is associated with a local audience located in a localmarket.
 17. The audience measurement apparatus of claim 15, wherein theprocessor is to: obtain a subset of the audience measurement data; andweight the subset based on a target demographic group represented in thepopulation data, a target program, a target date, and a targettime-of-day.
 18. The audience measurement apparatus of claim 15, whereinto combine the plurality of ratios, the processor is to: multiplyrespective ones of the plurality of ratios by corresponding ones of thethird audience metrics to determine fourth audience metrics; and sum thefourth audience metrics to determine the audience exposure metric. 19.The audience measurement apparatus of claim 15, wherein the processor isto: impute characteristics of the set-top box return path tuning data;add cutback indicators to the weighted data; determine a demographicaudience metric using the weighted data; determine a cutback audiencemetric using a portion of the weighted data having a cutback indicatorselected based on the set-top box return path tuning data; determine aset-top box audience metric using the set-top box return path tuningdata; and combine the demographic audience metric, the cutback audiencemetric and the set-top box audience metric to form the audience exposuremetric.
 20. The audience measurement apparatus of claim 15, wherein theaudience measurement data is first audience measurement data, and theprocessor is to adjust the audience exposure metric based on secondaudience measurement data associated with the second geographic area andthat is different from the set-top box return path tuning data.